Transitive reduction for social network analysis and visualization

In this paper, we show that transitive reduction can be used in real, large social networks analysis. Transitive reduction is an edge-removing operation on directed graphs that preserves some important properties and structures of the graph. After a presentation of this tool interest, we show its properties and how to use it. An application of the process on a real-word large social network (public and famous Enron corpus) built upon interaction data (email boxes) validates this approach.